statistics/slides.org
author bhanu
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#+LaTeX_CLASS: beamer
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#+LaTeX_CLASS_OPTIONS: [presentation]
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#+BEAMER_FRAME_LEVEL: 1
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#+BEAMER_HEADER_EXTRA: \usetheme{Warsaw}\usecolortheme{default}\useoutertheme{infolines}\setbeamercovered{transparent}
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#+COLUMNS: %45ITEM %10BEAMER_env(Env) %10BEAMER_envargs(Env Args) %4BEAMER_col(Col) %8BEAMER_extra(Extra)
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#+PROPERTY: BEAMER_col_ALL 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 :ETC
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#+LaTeX_CLASS: beamer
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#+LaTeX_CLASS_OPTIONS: [presentation]
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#+LaTeX_HEADER: \usepackage[english]{babel} \usepackage{ae,aecompl}
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#+LaTeX_HEADER: \usepackage{mathpazo,courier,euler} \usepackage[scaled=.95]{helvet}
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#+LaTeX_HEADER: \usepackage{listings}
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#+LaTeX_HEADER:\lstset{language=Python, basicstyle=\ttfamily\bfseries,
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#+LaTeX_HEADER:  commentstyle=\color{red}\itshape, stringstyle=\color{darkgreen},
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#+LaTeX_HEADER:  showstringspaces=false, keywordstyle=\color{blue}\bfseries}
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#+TITLE: Statistics
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#+AUTHOR: FOSSEE
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#+DATE
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#+EMAIL:     info@fossee.in
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#+DESCRIPTION: 
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#+KEYWORDS: 
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#+LANGUAGE:  en
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#+OPTIONS:   H:3 num:nil toc:nil \n:nil @:t ::t |:t ^:t -:t f:t *:t <:t
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#+OPTIONS:   TeX:t LaTeX:nil skip:nil d:nil todo:nil pri:nil tags:not-in-toc
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* Outline 
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 - Doing statistical operations in Python  
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   - Summing set of numbers
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   - Finding there mean
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   - Finding there Median
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   - Finding there Standard Deviation 
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* Data set
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  - A;015163;JOSEPH RAJ S;083;042;47;00;72;244;;; 
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  The following are the fields in any given line.
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   - Region Code which is 'A'
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   - Roll Number 015163
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   - Name JOSEPH RAJ S
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   - Marks of 5 subjects: -- English 083 -- 
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     Hindi 042 -- Maths 47 --
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     Science 35 -- Social 72
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   - Total marks 244
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* Question
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  - In the given file football.txt at path /home/fossee/football.txt , 
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    one column is player name,second is goals at home 
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    and third goals away.
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    - Find the total goals for each player
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    - Mean home and away goals
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    - Standard deviation of home and away goals 
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* Solution
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#+begin_src python
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  L=loadtxt('/home/amit/football.txt',usecols=(1,2),
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            delimiter=',')
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  sum(L,1)
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  mean(L,0)
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  std(L,0)
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#+end_src python
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* Summary 
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  - sum
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  - mean
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  - median
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  - std
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